MétaCan
Menu
Back to cohort
Record W4386525347 · doi:10.56952/arma-2023-0285

Development of a Novel Dynamic Formation Stimulation Technique: FDEM-Based Numerical Modelling Results

2023· article· en· W4386525347 on OpenAlexaff
A. Lisjak, O. K. Mahabadi, Jane Lund Andersen, J. Hinkey, Emmanuel Detournay, E. Araujo, Rigoberto Rimmelin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsGeomechanica (Canada)
Fundersnot available
KeywordsBoreholeGeologyHydraulic fracturingOverburdenFracture (geology)Geotechnical engineeringTight gasParametric statisticsCabin pressurizationGeothermal gradientPore water pressurePetroleum engineeringGeophysicsEngineering

Abstract

fetched live from OpenAlex

ABSTRACT The goal of this paper is to provide an overview of numerical simulation results aiding the development of a novel pulsed combustion-based wellbore fracturing technology. The technology can be used as a pre-conditioning and stimulation tool for in-situ recovery and cave mining, enhanced geothermal systems, and unconventional hydrocarbon reservoirs. Numerical simulations were carried out using a finite-discrete element method (FDEM) code, capable of explicit consideration of rock fracturing processes and dynamic phenomena. A parametric study on the effect of borehole pressurization characteristics and geostatic confinement highlighted the influence of these factors on fracture complexity and radial extent. An in-depth analysis of the extent of the crushed zone and radial distributions of fracture specific surface area was carried out. Borehole pair configurations were simulated to investigate borehole spacing and loading sequence effects. The simulations provided the following key findings: (a) for a set of fracturing parameters there exists a maximum borehole spacing beyond which fracture networks no longer intersect; (b) simultaneous fracturing of borehole pairs produces a compounding effect that induces higher inter-borehole fracturing compared to sequential fracturing; (c) the incorporation of a coupled in-fracture gas pressure propagation logic has substantial positive effects on the radius of the induced fractured zone. INTRODUCTION Rock mass stimulation techniques are used in several geomechanical applications such as cave mining, in-situ recovery (ISR) or leaching (ISL) mining, enhanced geothermal systems (EGSs), and unconventional hydrocarbon recovery. Application of conventional, hydraulic-based stimulations to deep, hard rock formations is limited by surface pumping pressures, as hydraulic fracturing techniques are unable to achieve breakdown in high strength rocks subject to large geostatic confinement. In addition, they may be unable to achieve complex formation fracturing characteristics, which are required for applications such as ISR mining and EGS. To overcome the limitations of conventional surface pumping stimulations, a new technology is being developed by NaturaFrac using surface injection of reactive gasses and subsequent subsurface dynamic combustion. The proposed downhole combustion-based dynamic pressurization technology allows to generate a wide range of in-situ pressures (exceeding ∼700 MPa), allowing to create a variety of desirable fracture responses depending on pressure rise rate and peak pressurization levels. Unlike other steady combustion or propellant-based fracturing approaches, the proposed method allows to readily change peak combustion pressure, pressurization rate, pulse duration, and number of applied pulses without having to retrieve the tool to surface in between applications or to change combustion parameters. As illustrated below in Fig. 1, pulsed combustion has advantages over alternative well bore fracturing techniques. Conventional hydraulic fracturing will typically produce a simple bi-wing or planar fracture system highly sensitive to the local well bore stress state and requires surface-generated high fluid pressures to overcome the effective formation strength (break-down pressure). Propellant fracturing can produce a complex initial fracturing pattern via very high dynamic pressures which tend to ignore the local stress state conditions (Cuderman, 1981) but is essentially a single pulse technology that requires the fracturing tool to be removed, reloaded at the surface and re-inserted to apply a subsequent pulse to drive fracture extension. Furthermore, it is not easily (or at all) dynamically tunable for pressure peak or pressurization rates matched to the formation characteristics/well bore stress state. Explosives-based fracturing is related to propellant fracturing, but the pressurization rates and peak values tend to be extremely high, thus producing significant near bore formation damage with short tensile fracture extension and cannot easily provide multiple applications without removal from and re-insertion into the wellbore (Kutter and Fairhurst, 1971, Donzé et al., 1997, Cho and Kaneko, 2004). Multi-pulsed-combustion-based fracturing (i.e., the NaturaFrac technology) combines the down-hole energetics of propellant and explosives but allows for single and multi-pulse dynamic pressure generation with tunable pressurization rates and pressure peaks depending on the dynamic fracturing requirements of the local well bore state. In addition, since the combustible gases are separately supplied from the surface a tool can apply multiple, changeable pulses to the same section of the well bore for generating additional fracture complexity and/or further extend the fracture network.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.256
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicRock Mechanics and ModelingFrench-language works237,207